Paper Citation Record · LEDGER

Memorization and Regularization in Generative Diffusion Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2501.15785.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.15785 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T04:53:14.333220Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-02T23:57:28.827531Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 30f31c8b-790c-40ef-a763-4de7609effec · inbound

Taking a Big Step: Large Learning Rates in Denoising Score Matching Prevent Memorization cites this paper.

Taking a Big Step: Large Learning Rates in Denoising Score Matching Prevent Memorization Memorization and Regularization in Generative Diffusion Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-09T04:53:14.333220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fca02d5c-1b07-4330-bb39-5b442a48a99d · inbound

When and how can inexact generative models still sample from the data manifold? cites this paper.

When and how can inexact generative models still sample from the data manifold? Memorization and Regularization in Generative Diffusion Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T22:07:58.014891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df378c41-77ba-4a7f-b757-46565de89c38 · inbound

On The Hidden Biases of Flow Matching Samplers cites this paper.

On The Hidden Biases of Flow Matching Samplers Memorization and Regularization in Generative Diffusion Models

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-16T21:11:16.929065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 676be107-b330-4e8d-ac2a-b35d73a0eec1 · inbound

A Kinetic Energy Perspective of Flow Matching cites this paper.

A Kinetic Energy Perspective of Flow Matching Memorization and Regularization in Generative Diffusion Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T03:31:36.818911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43c60527-dfaf-4f1d-b17e-0475f907abce · inbound

Conditional flow matching for physics-constrained inverse problems with finite training data cites this paper.

Conditional flow matching for physics-constrained inverse problems with finite training data Memorization and Regularization in Generative Diffusion Models

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-15T10:59:57.381972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0fed71cf-5b2d-4864-8455-1202e1c7199d · inbound

On the Memorization of Consistency Distillation for Diffusion Models cites this paper.

On the Memorization of Consistency Distillation for Diffusion Models Memorization and Regularization in Generative Diffusion Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:11:11.008730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e385735f-4eae-4396-bce2-eacdadde45e6 · inbound

Tessellations of Semi-Discrete Flow Matching cites this paper.

Tessellations of Semi-Discrete Flow Matching Memorization and Regularization in Generative Diffusion Models

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T03:10:53.719942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 560f1f63-88d0-44a7-83bd-f5e09cb29abd · inbound

Evaluating the Representation Space of Diffusion Models via Self-Supervised Principles cites this paper.

Evaluating the Representation Space of Diffusion Models via Self-Supervised Principles Memorization and Regularization in Generative Diffusion Models

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-02T23:57:28.829434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 27b71681-948e-4fcf-b4ea-fda4f4a11e14 · inbound

PAC-DP: PAC-Bayesian Diffusion Policy Learning cites this paper.

PAC-DP: PAC-Bayesian Diffusion Policy Learning Memorization and Regularization in Generative Diffusion Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-31T18:58:09.295427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.